A tunneling speed enhancement method for super-large-diameter shield machines considering strata heterogeneity
Tunnelling and Underground Space Technology,
Год журнала:
2025,
Номер
159, С. 106496 - 106496
Опубликована: Фев. 27, 2025
Язык: Английский
Selection Method and Application of Dual‐Mode TBM in Composite Strata: A Case Study of Shenzhen Metro Line 14
Advances in Civil Engineering,
Год журнала:
2025,
Номер
2025(1)
Опубликована: Янв. 1, 2025
With
the
continuous
development
of
urban
railway
construction,
metro
tunnels
tend
to
cross
complex
geological
formations.
Single‐mode
tunnel
boring
machines
(TBMs),
typically
designed
accommodate
a
specific
type
rock
mass,
often
encounter
severe
eccentric
cutter
wear
and
attitude
deflection,
when
tunneling
in
composite
strata.
The
inadequate
support
pressure
exerted
by
TBM
under
single
excavation
mode
that
fails
balance
soil
water
weak
strata
may
result
collapse
face.
dual‐mode
equipment,
which
has
flexible
adaptability
environment
could
be
potential
solution
problems
longitudinal
However,
traditional
selection
methods
mainly
focus
on
influence
parameters
an
individual
stratum,
according
empirical
analysis.
While
requires
comprehensive
consideration
combined
effects
efficiency,
duration,
cost
related
distribution
different
Based
comparison
projects
using
equipment
worldwide
their
parameters,
fundamental
principles
were
proposed
this
research.
A
fuzzy
evaluation
model
was
developed
for
earth
balanced
(EPB)
open
cutting
determine
limit
length
each
section
adjustment.
Finally,
case
study
Shenzhen
Metro
Line
14
presented
verify
innovative
method
TBM.
results
show
are
consistent
with
actual
project,
based
field‐obtained
operational
parameters.
Язык: Английский
A physics-data-driven method for predicting surface and building settlement induced by tunnel construction
Computers and Geotechnics,
Год журнала:
2024,
Номер
179, С. 107020 - 107020
Опубликована: Дек. 25, 2024
Язык: Английский
Rapid Prediction of Cutterhead Torque in Hard-Rock Tunneling Using IEWOA-TSVD-ITELM
IEEE Access,
Год журнала:
2024,
Номер
12, С. 88658 - 88680
Опубликована: Янв. 1, 2024
Язык: Английский
A singular spectrum analysis-enhanced BiTCN-selfattention model for runoff prediction
Earth Science Informatics,
Год журнала:
2024,
Номер
18(1)
Опубликована: Дек. 12, 2024
Язык: Английский
Geological adaptive intelligent control of earth pressure balance shield machine based on deep reinforcement learning
Artificial Intelligence Review,
Год журнала:
2024,
Номер
57(8)
Опубликована: Июль 27, 2024
Abstract
Scientific
and
precise
control
of
tunnelling
parameters
is
utmost
importance
during
the
construction
shield
machines.
Given
complexity
working
environment,
manual
operation
highly
prone
to
causing
safety
accidents.
Therefore,
achieving
intelligent
machine
crucial.
Based
on
this,
this
paper
proposes
a
geological
adaptive
method
earth
pressure
balance
using
Deep
Deterministic
Policy
Gradient
(DDPG)
algorithm
as
framework,
with
Actor-Critic
basis.
Firstly,
DDPG
agent
constructed
replace
screw
conveyor
system
main
body
strategy
implementation.
Secondly,
an
environmental
model
established
by
utilizing
mechanism
between
sealed
cabin
speed.
The
real-time
pressure,
target
error
serve
state
space,
while
speed
used
action
space.
A
combined
reward
function
set
based
accuracy.
Finally,
Actor
network
interacts
environment
under
supervision
Critic
network.
Successful
training
achieved
when
cumulative
value
maximized,
resulting
in
output
optimal
strategy.
In
paper,
dynamically
regulates
interacting
realize
ensure
dynamic
excavation
face
pressure.
test
results
show
that
has
good
effect
various
conditions,
can
complete
72
kinds
soil
transition
tasks.
It
strong
adaptability
respond
well
changes
conditions.
This
approach
enhances
intelligence
machine,
mitigating
inaccuracies
attributed
human
operation,
which
provides
guarantee
safe
whilst
exhibiting
valuable
engineering
applications.
Язык: Английский